Resource: LORELEI Ukrainian Representative Language Pack
|Reference||LORELEI Ukrainian Representative Language Pack|
|Date of Submission||Nov. 16, 2020, 9:28 p.m.|
|Resource Type||Primary Text|
|Media Type||Text, Software|
|Format/MIME Type||application/xml, text/plain|
|Access Medium||Web Download|
LORELEI Ukrainian Representative Language Pack consists of Ukrainian monolingual text, Ukrainian-English parallel and comparable text, annotations, supplemental resources and related software tools developed by the Linguistic Data Consortium for the DARPA LORELEI program.
The LORELEI (Low Resource Languages for Emergent Incidents) program was concerned with building human language technology for low resource languages in the context of emergent situations like natural disasters or disease outbreaks. Linguistic resources for LORELEI include Representative Language Packs and Incident Language Packs for over two dozen low resource languages, comprising data, annotations, basic natural language processing tools, lexicons and grammatical resources. Representative languages were selected to provide broad typological coverage, while incident languages were selected to evaluate system performance on a language whose identity was disclosed at the start of the evaluation.
Ukrainian is spoken mainly in Ukraine. Data was collected in the following genres: discussion forum, news, reference, social network, and weblog. Both monolingual text collection and parallel text creation involved a combination of manual and automatic methods.
Data volumes are as follows:
* 111 million words of Ukrainian monolingual text, approximately 700,000 words of which were translated into English
Approximately 75,000 words were annotated for named entities, and up to 50,000 words contain additional annotation, including situation frames (identifying entities, needs and issues) and entity detection and linking.
Lexical resources and software tools are also included in this release. The tools recreate source data from the processed XML material, condition text data users download from Twitter, apply sentence segmentation to raw text and tag named entities.
Monolingual and parallel text are presented in XML with associated dtds. Annotation data is presented as tab delimited files. All text is UTF-8 encoded.
The knowledge base for entity linking annotation for this corpus and all LORELEI Representative Language and Incident Language Packs is available separately as LORELEI Entity Detection and Linking Knowledge Base (LDC2020T10).
This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR0011-15-C-0123. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of DARPA.
|Creator||Xiaoyi Ma , David Graff , Jonathan Wright , Stephanie Strassel , Jennifer Tracey , Seth Kulick , Michael Arrigo , Neville Ryant , Song Chen , Dana Delgado|
|Distributor||Linguistic Data Consortium|
|Rights Holder||Portions See LDC Catalog entry for copyright statement.|